Current fingerprint collection procedures have a number of drawbacks. Collecting ink prints is a messy and time consuming procedure often resulting in smearing. This lowers the fingerprint quality which significantly degrades matching performance.
U.S. Government agencies and the private sector have a need to rapidly capture a subject's fingerprints for identification or screening purposes, especially when processing large groups. This need for rapid collection as well as scenarios for first responders constrained by environmental or medical considerations dictate that the fingerprint collection uses a contactless means. Currently existing two-dimensional (“2D”) fingerprint scanners significantly lower fingerprint collection times, however they require the subject to touch a mechanism. Touch sensors are impractical and unsafe for emergency first responder operational scenarios.
Currently existing three-dimensional (“3D”) fingerprint scanners are capable of collecting at very limited standoff distances (contactless); however, these systems generate 3D fingerprint data using 2D images captured from multiple cameras surrounding the finger. As such, these systems are not robust to discoloration of the subject's fingertips and can be easily deceived by presenting the scanner with a fake 2D fingerprint image. Also, systems do not extract 2D fingerprint images from true 3D depth information.
Spatial phase imaging sensors are a recent breakthrough that allow the collection of high resolution mesh data on the fingertips. However, no known prior algorithms exist to extract 2D fingerprint from the mesh data alone.
An existing method for standoff 2D fingerprint extraction from 3D-like data operates by processing 2D images collected from multiple known camera views. Indeed, there are several existing methods for standoff 2D fingerprint extraction from 3D-like data. Both TBS Inc.'s and Anil Jain's approach operate by processing 2D images collected from multiple known camera views. These approaches are limited to single fingerprint collection and are quite different from the algorithms described in this document. Furthermore, both approaches require that single fingers are inserted into a cavity that is surrounded by cameras, offering limited standoff distances while imposing significant constraints on the subject being fingerprinted.
Flash Scan 3D Inc.'s and Daniel Lau's approach both employ a Structure Light Illumination (SLI) method for capturing 3D fingerprints from a single aperture camera. These non-contact 3D scanning systems use multiple digital cameras along with a DLP projector and claim to have the capability to capture all five fingers and palm prints in a single image collection. However, research into their approaches suggests that they are currently not able to image whole hand data with a single image collection.
The above techniques suffer quite a few drawbacks and are quite different from the embodiments described in this application. For example, these existing techniques are not robust to discoloration of the subject fingertips and deception methods such as presenting the system with a fake 2D fingerprint image.